Triple

T33381424
Position Surface form Disambiguated ID Type / Status
Subject Ecclesiastical Province of Manila E854791 entity
Predicate hasJurisdictionOver P808 FINISHED
Object Diocese of Cubao
The Diocese of Cubao is a Roman Catholic ecclesiastical territory in Quezon City, Philippines, serving a large urban population with numerous parishes and religious institutions.
E2085950 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Diocese of Cubao | Statement: [Ecclesiastical Province of Manila, hasJurisdictionOver, Diocese of Cubao]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Diocese of Cubao
Triple: [Ecclesiastical Province of Manila, hasJurisdictionOver, Diocese of Cubao]
Generated description
The Diocese of Cubao is a Roman Catholic ecclesiastical territory in Quezon City, Philippines, serving a large urban population with numerous parishes and religious institutions.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3496ca10c8190908640d18fa00832 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e002526881909ffee65161b1a6e1 completed May 3, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36cc5e09fc8190a61083bf245844cb completed June 20, 2026, 5:22 p.m.
NEDg Description generation batch_6a36ccc5f9f88190870df51553289a23 completed June 20, 2026, 5:24 p.m.
NED2 Entity disambiguation (via description) batch_6a36ce3e3e48819091aece379948e411 completed June 20, 2026, 5:30 p.m.
Created at: May 1, 2026, 1:35 a.m.